Urticaria Control Test real‐world performance: A post‐hoc analysis
Authors: Pascale Salameh, Annika Gutsche, Felix Aulenbacher, Thomas Buttgereit, Karsten Weller, Frank Siebenhaar, Marcus Maurer
Journal: Allergy (2023)

Chronic urticaria (CU) is a debilitating skin disease characterized by intensely itchy wheals, angioedema, or both for longer than 6 weeks.1 The Urticaria Control Test (UCT) is a validated patient-reported outcome measure (PROM) to assess disease control in CU2 over a recall period of 4 weeks. UCT includes four questions, related to physical symptoms (Q1), quality of life (Q2), treatment effect (Q3), and overall control (Q4) with five answer options each (scored 0–4 points), with a total score ranging from zero to 16.2 UCT validity was demonstrated in clinical trial settings,3, 4 but real-world data are largely missing. Thus, UCT scale validity and reliability should be confirmed in a real-world population, to inform and direct further use and support better clinical decision-making and patients' outcomes.5 To this end, we analyzed (SPSS; version 28.0) fully anonymized UCT data of 1357 CU patients at the Urticaria Center of Excellence and Reference (UCARE)-Berlin. Three methods were used to assess the structural validity of the scale: First, items (UCT questions), and sets of items were correlated with the total UCT score using the Spearman correlation, and Cronbachs alpha was calculated to assess consistency. Second, a stepwise multiple regression analysis, taking the UCT score as a dependent variable, was run with items as independent variables; r-squares assessed model fit. Third, a factor analysis using the principal component method re-explored the dimensionality of the items versus CU control concept, identifying whether items measure the same underlying construct (control of CU) and which items are most strongly related to it (Supplementary Material). Q1 and Q2 showed the highest correlation (.832), while other correlations were <.7. Internal consistency was similarly high for items' combinations (Table 1). Particularly, Q1 was the single item explaining most of the UCT outcome (82.4%), and combining Q1, Q3, and Q4 explained it best (97.4%; Table 1). By multiple regression, Q1 added most to the construct, whereas Q2 added the least, with R2 values of .824 and .022, respectively (Table 2). No single question was able to predict control without loss of information, but Q1 emerged as the most significant variable in predicting the UCT score. The combination (Q1, Q3, and Q4) was not significantly different from the four questions together, suggesting a halo effect for Q1 and Q2.6 The factor analysis, however, showed that Q2 is essential for explaining the underlying construct; all four questions were important as they loaded on the same component: Q1 (.919), Q2 (.911), Q3 (.763), and Q4 (.856); yet, Q1, Q2, and Q3 explained 78% of the latent construct (disease control), and adding Q4 did not explain it better (74.7%). Thus, all questions showed an appropriate correlation to the underlying construct. The substantial explanation of the underlying CU control by Q1, Q2, and Q3 without Q4 might be due to the wording of Q4, which added a subjective and global patient view on the CU Control concept, whereas the first three questions focus on more specific aspects of CU control, that is, disease activity (Q1), disease impact (Q2), and response to treatment (Q3). Taken together, our results show that all questions of the UCT are relevant in measuring disease control in CU, with relevance varying according to the statistical method used. The four questions of the UCT are complementary and necessary to measure disease control, and no question could be omitted without affecting the construct validity. The current work suggests that the four-question approach to assess disease control in CU should be retained. Future studies on different populations using different languages are necessary to further confirm this finding. MM generated the idea and supervised the work; PS overviewed the statistical analysis and wrote the manuscript draft; AG analyzed and interpreted the data; TB and KW contributed to the manuscript elaboration. All authors contributed to the manuscript's finalization and approved its final version. We thank Anja Lignau for help with project management. Intramural funding. PS, AG, and FA have no conflict of interest to declare. TB has no conflict of interest in relation to this work. Outside of it, TB is or recently was a speaker and/or advisor for and/or has received research funding from AstraZeneca, BioCryst, CSL-Behring, GSK, Hexal, KalVista, Medac, Novartis, Pharming, Roche, Sanofi, and Takeda. KW is or recently was a speaker and/or advisor for and/or has received research funding from Biomarin, CSL-Behring, Moxie, Novartis, and Takeda. FS is or recently was a speaker and/or advisor for and/or has received research funding from Allakos, Blueprint, Celldex, Cogent, Escient, Granular, GSK, Invea, Noucor, Novartis, Moxie, Sanofi/Regeneron, Third HarmonicBio. MM is or recently was a speaker and/or advisor for and/or has received research funding from Allakos, Alvotech, Amgen, Aquestive, Aralez, AstraZeneca, Bayer, Celldex, Celltrion, Evommune, GSK, Ipsen, Kyowa Kirin, Leo Pharma, Lilly, Menarini, Mitsubishi Tanabe Pharma, Moxie, Noucor, Novartis, Orion Biotechnology, Resonance Medicine, Sanofi/Regeneron, Septerna, Trial Form Support International AB, Third HarmonicBio, ValenzaBio, Yuhan Corporation, and Zurabio. Raw data were generated at Charite—Universitätsmedizin Berlin, Germany. Further data supporting the findings of this study are available from the corresponding author on request. 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